uratmangun · December 14, 2023 13:09
diff --git a/commitmessage.mjs b/commitmessage.mjs
 import { GoogleGenerativeAI } from "@google/generative-ai";
 import dotenv from 'dotenv';
 import {execa} from 'execa';
 dotenv.config();
 import ky from 'ky';

 const API_KEY = process.env.GOOGLE_API_KEY; // Replace with your actual API key
 const systemMessage=`You are a commit message generator by creating exactly one commit message by the diff strings without adding unnecessary information! Here is the format of a good commit message from https://karma-runner.github.io/6.4/dev/git-commit-msg.html guides:

 ---
 <type>(<scope>): <subject>
 <BLANK LINE>
 <body>
 ---

 With allowed <type> values are feat, fix, perf, docs, style, refactor, test, and build.`;
 const genAI = new GoogleGenerativeAI(API_KEY);
 async function listModel(){
    const response = await ky.get('https://generativelanguage.googleapis.com/v1beta/models?key='+API_KEY).json();
    return response
 }

 async function countToken(text) {
    try {
      const response = await ky.post('https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:countTokens?key='+API_KEY, {
        headers: {
          'Content-Type': 'application/json'
        },
        json: {
          contents: [{
            parts: [{
              text
            }]
          }]
        }
      }).json();
  
      console.log(response);
    } catch (error) {
      console.error(error);
    }
  }
 async function run() {
 const allModel=await listModel();
 const geminiProTokenLimit=allModel.models[3].inputTokenLimit;
 const {stdout} = await execa('git', ['diff'])

  const model = genAI.getGenerativeModel({ model: "gemini-pro"});
  const chat = model.startChat({
    history: [
        {
            role: "user",
            parts: systemMessage,
          },
      {
        role: "model",
        parts: `fix(middleware): ensure Range headers adhere more closely to RFC 2616

        Add one new dependency, use \`range-parser\` (Express dependency) to compute range. It is more well-tested in the wild.`,
      },
      
    ]
  });
  const { totalTokens } = await model.countTokens(stdout);
 if(totalTokens<=geminiProTokenLimit){
    const msg = stdout;

    const result = await chat.sendMessage(msg);
    const response = await result.response;
    const text = response.text();
    console.log(text);
 }
  

 }

 run();
	import { GoogleGenerativeAI } from "@google/generative-ai";
	import dotenv from 'dotenv';
	import {execa} from 'execa';
	dotenv.config();
	import ky from 'ky';

	const API_KEY = process.env.GOOGLE_API_KEY; // Replace with your actual API key
	const systemMessage=`You are a commit message generator by creating exactly one commit message by the diff strings without adding unnecessary information! Here is the format of a good commit message from https://karma-runner.github.io/6.4/dev/git-commit-msg.html guides:

	---
	<type>(<scope>): <subject>
	<BLANK LINE>
	<body>
	---

	With allowed <type> values are feat, fix, perf, docs, style, refactor, test, and build.`;
	const genAI = new GoogleGenerativeAI(API_KEY);
	async function listModel(){
	const response = await ky.get('https://generativelanguage.googleapis.com/v1beta/models?key='+API_KEY).json();
	return response
	}

	async function countToken(text) {
	try {
	const response = await ky.post('https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:countTokens?key='+API_KEY, {
	headers: {
	'Content-Type': 'application/json'
	},
	json: {
	contents: [{
	parts: [{
	text
	}]
	}]
	}
	}).json();

	console.log(response);
	} catch (error) {
	console.error(error);
	}
	}
	async function run() {
	const allModel=await listModel();
	const geminiProTokenLimit=allModel.models[3].inputTokenLimit;
	const {stdout} = await execa('git', ['diff'])

	const model = genAI.getGenerativeModel({ model: "gemini-pro"});
	const chat = model.startChat({
	history: [
	{
	role: "user",
	parts: systemMessage,
	},
	{
	role: "model",
	parts: `fix(middleware): ensure Range headers adhere more closely to RFC 2616

	Add one new dependency, use \`range-parser\` (Express dependency) to compute range. It is more well-tested in the wild.`,
	},

	]
	});
	const { totalTokens } = await model.countTokens(stdout);
	if(totalTokens<=geminiProTokenLimit){
	const msg = stdout;

	const result = await chat.sendMessage(msg);
	const response = await result.response;
	const text = response.text();
	console.log(text);
	}


	}

	run();